Synopses & Reviews
"The aim of this book is to provide a correct and up-to-date understanding of--and appreciation for--the practical aspects of crucial, yet little-understood core database issues. It identifies and clarifies certain fundamental concepts, principles, and techniques that persistently trouble users and vendors. It assesses the treatment of those issues in SQL (both the standard and commercial implementations) and gives specific guidance and practical advice on how to deal with them (and how not to). It covers, carefully and thoroughly, several particularly tricky and misunderstood topics--complex data types, missing information, data hierarchies, quota queries, and so forth--in a succinct and concise form for the busy database practitioner."
--C. J. Date
Three decades ago relational technology put the database field on a sound, scientific foundation for the first time. But the database industry--vendors, users, experts, and the trade press--has essentially flouted its principles, focusing instead on a "cookbook," product-specific approach, devoid of conceptual understanding. The consequences have been costly: DBMS products, databases, development tools, and applications don't always perform up to expectation or potential, and they can encourage the wrong questions and provide the wrong answers.
Practical Issues in Database Management is an attempt to remedy this intractable and costly situation. Written for database designers, programmers, managers, and users, it addresses the core, commonly recurring issues and problems that practitioners--even the most experienced database professionals--seem to systematically misunderstand, namely:
- Unstructured data and complex data types
- Business rules and integrity enforcement
- Keys
- Duplicates
- Normalization and denormalization
- Entity subtypes and supertypes
- Data hierarchies and recursive queries
- Redundancy
- Quota queries
- Missing information
Fabian Pascal examines these critical topics thoroughly, comparing the severe costs of mishandling them to the practical benefits of implementing the correct solutions. With an emphasis on both principles and practice,
Practical Issues in Database Management employs real-world examples to provide an assessment of current technology--SQL and the DBMS products based on it--and, whenever possible, offers concrete recommendations and workarounds. With the insight provided by
Practical Issues in Database Management , you will be in a far better position to evaluate specific products, exploit their capabilities, and avoid their deficiencies.
0201485559B04062001
Synopsis
Databasics clearly explains the key concepts users and database professionals need to understand in order to build well-designed databases that answer business questions accurately and efficiently. Fabian Pascal, one of the industry's leading experts, identifies ten critical, recurring issues that both database users and vendors often fail to address appropriately. Pascal demonstrates why understanding these fundamentals is so important, providing detailed examples and solutions designed to help users escape the key pitfalls of database development. Among the topics covered: unstructured data and complex data types; business rules and enforcing data integrity; keys; duplicates; normalization; entity subtypes and supertypes; data hierarchies and recursive queries; redundancy; quota queries; and how to handle missing information. Along the way, Pascal offers no-holds-barred assessments of how well current SQL implementations and commercial products address each issue. Databasics, in short, is a complete guide to building databases right the first time, so they don't have to be rebuilt later. For all DBAs, developers, managers, and end-users that need to understand the best ways to design and implement database systems.
Synopsis
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About the Author
Fabian Pascal is an independent industry analyst, consultant, author, and lecturer specializing in database management. He is the author of two previous books,
Understanding Relational Databases and
SQL and Relational Basics, and has contributed extensively to many industry publications.
0201485559AB04062001
Table of Contents
Foreword.
Preface.
1. Careful What You Wish For: Data Types and Complexity.
The Issue.
Fundamentals.
“Simple” Types.
System-Defined Types.
User-Defined Types.
Data Type Support.
On Type “Atomicity.”
“Complex” Types.
Practical Implications.
Relational Domains versus Object Classes.
Database Design.
Relational Structure versus Object Manipulation.
DBMS Implementation.
“Domains.”
“Universal” DBMSs.
Conclusion and Recommendations.
Appendix 1A: Possible Representations for Image Types.
Appendix 1B: Graphics File Follies.
Appendix 1C: Biometric Tools Ready to Take Off.
Appendix 1D: Search Engine Failures.
Appendix 1E: “Complex” Types and Operators: An Internet Illustration.
Appendix 1F: Java and Database Synergy.
2. The Rule of Rules: Integrity.
The Issue.
Fundamentals.
Business Rules.
Integrity Constraints.
Domain Constraints.
Column Constraints.
Table Constraints.
Database Constraints.
Database Correctness.
Base versus Derived Constraints.
Integrity Enforcement.
Integrity Rules.
DBMS Support.
Practical Implications.
SQL and Integrity.
Domain Rules.
Column Rules.
Table and Database Rules.
Procedural Support.
Conclusion and Recommendations.
Appendix 2A: A Note on SQL's OVERLAPS Operator.
3. A Matter of Identity: Keys.
The Issue.
Fundamentals.
Simple versus Composite Keys.
Natural versus Surrogate Keys.
Candidate versus Primary Keys.
Foreign Keys.
Referential Integrity and Primary Keys.
DBMS Support.
Practical Implications.
SQL and Keys.
Conclusion and Recommendations.
4. Don't Get Duped by Dupes: Duplicate Rows.
The Issue.
Fundamentals.
Determining Entity Types.
“Hidden” Information.
A Relational Bonus.
Practical Implications.
SQL and Duplicates.
Duplicate Removal.
Countability.
Addressability.
Correctness and Interpretability of Results.
Essential Order and Performance Optimization.
Conclusion and Recommendations.
Appendix 4A: Duplicate Removal in SQL.
Appendix 4B: Language Redundancy and Duplicates.
5. The Key, the Whole Key, and Nothing but the Key: Normalization.
The Issue.
Fundamentals.
Repeating Groups.
First Normal Form.
Column Dependencies.
Functional Dependencies.
Second Normal Form.
Third Normal Form.
Multivalued Dependencies.
Fourth Normal Form.
Join Dependencies.
Fifth Normal Form.
Practical Implications.
SQL and Multivalued Columns.
“Denormalization” and Performance.
Conclusion and Recommendations.
6. Neither Distinct nor the Same: Entity Supertypes and Subtypes.
The Issue.
Fundamentals.
Entity Types, Attributes, and Relationships.
A Special Case.
DBMS Support.
Practical Implications.
Multikey References.
SQL Subtables and Supertables.
Conclusion and Recommendations.
7. Climbing Trees in SQL: Data Hierarchies.
The Issue.
Fundamentals.
Nodes and Links.
“Explode” Queries.
Recurring Nodes.
Practical Implications.
SQL and Trees.
Conclusion and Recommendations.
8. Not Worth Repeating: Redundancy.
The Issue.
Fundamentals.
Duplicate Rows.
Within-Table Duplicates.
Cross-Table Duplicates.
Entity Subtypes and Supertypes.
Column Dependencies.
Functional Dependencies.
Dependency on Part of the Key.
Indirect Dependency.
Multivalued Dependencies.
Join Dependencies.
Derived Information.
Redundancy Control.
Denormalized Designs.
Derived Information.
Practical Implications.
SQL and Keyless Tables.
SQL and Cross-Table Duplicates.
SQL and “Denormalization.”
SQL and Derived Information.
Conclusion and Recommendations.
9. Will SQL Come to Order: Quota Queries.
The Issue.
Fundamentals.
Ambiguities.
The Declarative Solution.
Practical Implications.
SQL and Quota Queries.
Conclusion and Recommendations.
10. What You Don't Know Can Hurt You: Missing Information.
The Issue.
Fundamentals.
Meaningless Assertions.
Empty Assertions.
Missing Information as Metadata.
DBMS Support.
Many-Valued Logic.
Practical Implications.
SQL NULLs.
NULLs and 4VL.
NULLs and 3VL.
2VL and Metadata.
Conclusion and Recommendations.
Index. 0201485559T04062001